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Mexico

AI Transparency & Explainability

The Open Loop Mexico program was a collaborative effort between Meta, C Minds, and the Inter-American Development Bank (IDB) to develop a governance framework and a practical playbook for transparency and explainability (T&E) in AI systems. The program involved working with a group of 10 Mexican companies that use AI to test the prototype and provide feedback. The overarching goal was to strengthen responsible AI in Mexico by promoting T&E practices.

Deployment Period | February - August 2021

The Open Loop Mexico program was a collaborative effort between Meta, C Minds, and the Inter-American Development Bank (IDB) to develop a governance framework and a practical playbook for transparency and explainability (T&E) in AI systems. The program involved working with a group of 10 Mexican companies that use AI to test the prototype and provide feedback. The overarching goal was to strengthen responsible AI in Mexico by promoting T&E practices.

Deployment Period | February - August 2021

Read the report now! 

MEXICO | August 2023

This report unveils the outcomes and strategic insights from the Open Loop Mexico program on AI Transparency and Explainability. The initiative focused on crafting and testing a Public Policy Prototype on the Transparency and Explainability of Artificial Intelligence Systems, including Automated Decision-Making (ADM) systems. The program's core objectives were:

  • To develop a governance framework and a practical playbook outlining the principles of transparency and explainability.
  • To ensure users can recognize when they are interacting with an AI/ADM system and understand its functionality and limitations.

Download the report:

PROGRAM DETAILS

Main Findings & Recommendations

The program's outcomes resulted in several notable recommendations to enhance transparency and explainability in AI systems, including:

Clarity and Effectiveness

Emphasizing the importance of clear communication and comprehension of AI system internal workings for users and stakeholders.

Viability

Ensuring the benefits of transparency and explainability outweigh the associated costs and implementation efforts.

Comprehensive Explanations

Encouraging companies to provide concise and easily understandable explanations of their AI systems, including decision-making rationale and data processing details.

Integration with User Experience

Incorporating transparency and explainability messages seamlessly into the user journey, including notifications, messages, and visual aids.

Partners & Observers

The program was a collaborative effort involving Meta, C Minds’ Eon Resilience Lab, the Inter-American Development Group (IDB) through its fAIr LAC initiative with the support of Mexico’s National Institute for Transparency, Access to Information and Personal Data Protection (INAI). This partnership was instrumental in aligning the program with national transparency and data protection standards and priorities.

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